Recent Advances in Breast Cancer Screening

A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Oncology".

Deadline for manuscript submissions: 15 July 2024 | Viewed by 2235

Special Issue Editors

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Guest Editor
Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
Interests: breast cancer

Special Issue Information

Dear Colleagues,

Breast cancer is the most prevalent cancer among women worldwide. In recent decades, substantial advances in breast imaging have provided improved methods for reaching early diagnosis, increasing the survival rates in women with breast cancer.

As breast imaging technologies have become more advanced, radiologists have gained the ability to detect the smallest of malignancies at very early stages; now more than ever, women have a fighting chance against breast cancer. Particularly, advances in medical imaging and genetic knowledge and the introduction of artificial intelligence technology in radiological practice have paved the way to true personalized medicine.

Mammography is currently the only screening test that has been shown to reduce breast cancer-related mortality. However, the large amount of mammography produced every year, the consequent high proportion of false-negative and false-positive results reported, and the shortage of trained radiologists capable of interpreting these exams are just part of the screening management problem, leading to additional economical costs and inequalities between low- and high-income countries.

Recently, mammography by full-field digital mammography systems, including digital breast tomosynthesis and contrast-enhanced spectral mammography, optimized the lesion to background contrast with resultant improvement in the sensitivity of the technique for cancer detection, facilitated by computer-aided detection.

Advances in ultrasound (including automated breast ultrasound) also have the potential to greatly improve the specificity of breast imaging with regard to cancer detection and lesion characterization.

Additionally, several large studies indicate that magnetic resonance imaging (MRI) has a role in early diagnosis of high-risk patients, in addition to its role in staging (facilitating the choice of the most appropriate surgery) and in the assessment of the response to chemotherapy and endocrine therapy.

Such advances in medical imaging together with the introduction of artificial intelligence technology in radiological practice have paved the way to a true personalized medicine. As clinicians gather more and better evidence of how effective these technologies are, they are consistently re-evaluating their methods in an effort to provide a more personalized approach to breast cancer screening based on patients’ individual risk factors.

For this Special Issue, we are soliciting original studies, meta-analysis, reviews, pictorial review, and letters investigating the new frontiers of breast cancer screening.

Dr. Anna Rotili
Dr. Filippo Pesapane
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Medicina is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • breast cancer
  • cancer screening
  • breast screening
  • breast imaging
  • oncology
  • mammography
  • magnetic resonance imaging
  • contrast enhanced mammography
  • ultrasound
  • personalized medicine
  • radiomics
  • artificial intelligence

Published Papers (1 paper)

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13 pages, 923 KiB  
Future Directions in the Assessment of Axillary Lymph Nodes in Patients with Breast Cancer
by Filippo Pesapane, Luciano Mariano, Francesca Magnoni, Anna Rotili, Davide Pupo, Luca Nicosia, Anna Carla Bozzini, Silvia Penco, Antuono Latronico, Maria Pizzamiglio, Giovanni Corso and Enrico Cassano
Medicina 2023, 59(9), 1544; - 25 Aug 2023
Cited by 2 | Viewed by 1782
Background and Objectives: Breast cancer (BC) is a leading cause of morbidity and mortality worldwide, and accurate assessment of axillary lymph nodes (ALNs) is crucial for patient management and outcomes. We aim to summarize the current state of ALN assessment techniques in [...] Read more.
Background and Objectives: Breast cancer (BC) is a leading cause of morbidity and mortality worldwide, and accurate assessment of axillary lymph nodes (ALNs) is crucial for patient management and outcomes. We aim to summarize the current state of ALN assessment techniques in BC and provide insights into future directions. Materials and Methods: This review discusses various imaging techniques used for ALN evaluation, including ultrasound, computed tomography, magnetic resonance imaging, and positron emission tomography. It highlights advancements in these techniques and their potential to improve diagnostic accuracy. The review also examines landmark clinical trials that have influenced axillary management, such as the Z0011 trial and the IBCSG 23-01 trial. The role of artificial intelligence (AI), specifically deep learning algorithms, in improving ALN assessment is examined. Results: The review outlines the key findings of these trials, which demonstrated the feasibility of avoiding axillary lymph node dissection (ALND) in certain patient populations with low sentinel lymph node (SLN) burden. It also discusses ongoing trials, including the SOUND trial, which investigates the use of axillary ultrasound to identify patients who can safely avoid sentinel lymph node biopsy (SLNB). Furthermore, the potential of emerging techniques and the integration of AI in enhancing ALN assessment accuracy are presented. Conclusions: The review concludes that advancements in ALN assessment techniques have the potential to improve patient outcomes by reducing surgical complications while maintaining accurate disease staging. However, challenges such as standardization of imaging protocols and interpretation criteria need to be addressed. Future research should focus on large-scale clinical trials to validate emerging techniques and establish their efficacy and cost-effectiveness. Over-all, this review provides valuable insights into the current status and future directions of ALN assessment in BC, highlighting opportunities for improving patient care. Full article
(This article belongs to the Special Issue Recent Advances in Breast Cancer Screening)
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